Detection of knee synovitis using non-contrast-enhanced qDESS compared with contrast-enhanced MRI

Background: To assess diagnostic accuracy of quantitative double-echo in steady-state (qDESS) MRI for detecting synovitis in knee osteoarthritis (OA). Methods: Patients with different degrees of radiographic knee OA were included prospectively. All underwent MRI with both qDESS and contrast-enhanced T1-weighted magnetic resonance imaging (CE-MRI). A linear combination of the two qDESS images can be used to create an image that displays contrast between synovium and the synovial fluid. Synovitis on both qDESS and CE-MRI was assessed semi-quantitatively, using a whole-knee synovitis sum score, indicating no/equivocal, mild, moderate, and severe synovitis. The correlation between sum scores of qDESS and CE-MRI (reference standard) was determined using Spearman’s rank correlation coefficient and intraclass correlation coefficient for absolute agreement. Receiver operating characteristic analysis was performed to assess the diagnostic performance of qDESS for detecting different degrees of synovitis, with CE-MRI as reference standard. Results: In the 31 patients included, very strong correlation was found between synovitis sum scores on qDESS and CE-MRI (ρ = 0.96, p < 0.001), with high absolute agreement (0.84 (95%CI 0.14–0.95)). Mean sum score (SD) values on qDESS 5.16 (3.75) were lower than on CE-MRI 7.13 (4.66), indicating systematically underestimated synovitis severity on qDESS. For detecting mild synovitis or higher, high sensitivity and specificity were found for qDESS (1.00 (95%CI 0.80–1.00) and 0.909 (0.571–1.00), respectively). For detecting moderate synovitis or higher, sensitivity and specificity were good (0.727 (95%CI 0.393–0.927) and 1.00 (0.800–1.00), respectively). Conclusion: qDESS MRI is able to, however with an underestimation, detect synovitis in patients with knee OA

Nuclear Ground State Observables and QCD Scaling in a Refined Relativistic Point Coupling Model

We present results obtained in the calculation of nuclear ground state properties in relativistic Hartree approximation using a Lagrangian whose QCD-scaled coupling constants are all natural (dimensionless and of order 1). Our model consists of four-, six-, and eight-fermion point couplings (contact interactions) together with derivative terms representing, respectively, two-, three-, and four-body forces and the finite ranges of the corresponding mesonic interactions. The coupling constants have been determined in a self-consistent procedure that solves the model equations for representative nuclei simultaneously in a generalized nonlinear least-squares adjustment algorithm. The extracted coupling constants allow us to predict ground state properties of a much larger set of even-even nuclei to good accuracy. The fact that the extracted coupling constants are all natural leads to the conclusion that QCD scaling and chiral symmetry apply to finite nuclei.Comment: 44 pages, 13 figures, 9 tables, REVTEX, accepted for publication in Phys. Rev.

Measurement of the Nucleon Structure Function F2 in the Nuclear Medium and Evaluation of its Moments

We report on the measurement of inclusive electron scattering off a carbon target performed with CLAS at Jefferson Laboratory. A combination of three different beam energies 1.161, 2.261 and 4.461 GeV allowed us to reach an invariant mass of the final-state hadronic system W~2.4 GeV with four-momentum transfers Q2 ranging from 0.2 to 5 GeV2. These data, together with previous measurements of the inclusive electron scattering off proton and deuteron, which cover a similar continuous two-dimensional region of Q2 and Bjorken variable x, permit the study of nuclear modifications of the nucleon structure. By using these, as well as other world data, we evaluated the F2 structure function and its moments. Using an OPE-based twist expansion, we studied the Q2-evolution of the moments, obtaining a separation of the leading-twist and the total higher-twist terms. The carbon-to-deuteron ratio of the leading-twist contributions to the F2 moments exhibits the well known EMC effect, compatible with that discovered previously in x-space. The total higher-twist term in the carbon nucleus appears, although with large systematic uncertainites, to be smaller with respect to the deuteron case for n<7, suggesting partial parton deconfinement in nuclear matter. We speculate that the spatial extension of the nucleon is changed when it is immersed in the nuclear medium.Comment: 37 pages, 15 figure

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose: Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the "ClinVar low-hanging fruit" reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods: Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results: We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion: The "ClinVar low-hanging fruit" analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock.The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement number 779257. Data were analyzed using the RD-Connect Genome-Phenome Analysis Platform, which received funding from the EU projects RD-Connect, Solve-RD, and European Joint Programme on Rare Diseases (grant numbers FP7 305444, H2020 779257, H2020 825575), Instituto de Salud Carlos III (grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática), and ELIXIR Implementation Studies. The collaborations in this study were facilitated by the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies, one of the 24 European Reference Networks approved by the European Reference Network Board of Member States, cofunded by the European Commission. This project was supported by the Czech Ministry of Health (number 00064203) and by the Czech Ministry of Education, Youth and Sports (number - LM2018132) to M.M.S

Inherited variants in CHD3 show variable expressivity in Snijders Blok-Campeau syndrome

Purpose: Common diagnostic next-generation sequencing strategies are not optimized to identify inherited variants in genes associated with dominant neurodevelopmental disorders as causal when the transmitting parent is clinically unaffected, leaving a significant number of cases with neurodevelopmental disorders undiagnosed. Methods: We characterized 21 families with inherited heterozygous missense or protein-truncating variants in CHD3, a gene in which de novo variants cause Snijders Blok-Campeau syndrome. Results: Computational facial and Human Phenotype Ontology–based comparisons showed that the phenotype of probands with inherited CHD3 variants overlaps with the phenotype previously associated with de novo CHD3 variants, whereas heterozygote parents are mildly or not affected, suggesting variable expressivity. In addition, similarly reduced expression levels of CHD3 protein in cells of an affected proband and of healthy family members with a CHD3 protein-truncating variant suggested that compensation of expression from the wild-type allele is unlikely to be an underlying mechanism. Notably, most inherited CHD3 variants were maternally transmitted. Conclusion: Our results point to a significant role of inherited variation in Snijders Blok-Campeau syndrome, a finding that is critical for correct variant interpretation and genetic counseling and warrants further investigation toward understanding the broader contributions of such variation to the landscape of human disease

The detection of a strong episignature for Chung–Jansen syndrome, partially overlapping with Börjeson–Forssman–Lehmann and White–Kernohan syndromes

Chung-Jansen syndrome is a neurodevelopmental disorder characterized by intellectual disability, behavioral problems, obesity and dysmorphic features. It is caused by pathogenic variants in the PHIP gene that encodes for the Pleckstrin homology domain-interacting protein, which is part of an epigenetic modifier protein complex. Therefore, we hypothesized that PHIP haploinsufficiency may impact genome-wide DNA methylation (DNAm). We assessed the DNAm profiles of affected individuals with pathogenic and likely pathogenic PHIP variants with Infinium Methylation EPIC arrays and report a specific and sensitive DNAm episignature biomarker for Chung–Jansen syndrome. In addition, we observed similarities between the methylation profile of Chung–Jansen syndrome and that of functionally related and clinically partially overlapping genetic disorders, White–Kernohan syndrome (caused by variants in DDB1 gene) and Börjeson–Forssman–Lehmann syndrome (caused by variants in PHF6 gene). Based on these observations we also proceeded to develop a common episignature biomarker for these disorders. These newly defined episignatures can be used as part of a multiclass episignature classifier for screening of affected individuals with rare disorders and interpretation of genetic variants of unknown clinical significance, and provide further insights into the common molecular pathophysiology of the clinically-related Chung–Jansen, Börjeson–Forssman–Lehmann and White–Kernohan syndromes.</p

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.Peer Reviewe

A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors

IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment\u27s photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies >1 TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to 20% for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors